Identifying TP53 mutation carrier is critical to people with Li-Fraumeni syndrome for cancer prevention and survival improvement. A new method is needed for clinical counselors because of the limitations of current clinical criteria. LFSpro is built on a Mendelian model and estimates the TP53 mutation probability through Elston-Stewart algorithm with accuracy. Unlike previously used models, our model incorporates de novo mutation rate, which greatly improved estimation accuracy.
Follow LFSpro
Other Useful Business Software
Gen AI apps are built with MongoDB Atlas
MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of LFSpro!